A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.